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Gaurav Sharma

Prof. Gaurav  Sharma

Professor of Electrical and Computer Engineering; Professor of Computer Science
University of Rochester


University of Rochester
RC Box 270126
Rochester NY 14627-0126
United States

tel: (585) 275-7313
E-mail: gaurav.sharma@rochester.edu
Web: http://www.ece.rochester.edu/~gsharma/

Area of Expertise

Media Security, Computer Vision, Image Processing, Color Imaging, Signal processing for Bioinformatics/Communications

Biography

Gaurav Sharma is with the University of Rochester, where he is a Professor in the Departments of Electrical and Computer Engineering, Computer Science, and Biostatistics and Computational Biology. From 2008-2010, he served as the Director for the Center for Emerging and Innovative Sciences (CEIS), a New York state supported center for promoting joint university-industry research and technology development, which is housed at the University of Rochester. From 1996 through 2003, he was with Xerox Research and Technology in Webster, NY first as a member of research and technology staff and then as a Principal Scientist and Project Leader.  Dr. Sharma is a fellow of SPIE, a fellow of the IEEE, and a fellow of the Society for Imaging Science and Technology (IS&T). He served as the Editor-in-Chief for the Journal of Electronic Imaging from 2011 through 2015. He has authored over 180 research articles and is the editor of the "Digital Color Imaging Handbook" published by CRC press.

Lecture Title(s)

Imaging Arithmetic: Physics U Math > Physics + Math

Via several case studies and visual demonstrations in the fields of color and digital imaging, this broadly accessible talk highlights how the combination of physical modeling and mathematical modeling can yield a “whole that is greater than the sum of the parts.” The talk is also accessible to STEM students at a high school level.

The Dimensions of Color

This visual presentation provides an introduction to color science and engineering particularly highlighting how dimensionality plays a role in perception for normal and color deficient individuals, in illumination, and in the regular and multiprimary displays.

Watermarking for Printed and Digital Images: Concepts and Applications

In this talk, we highlight digital watermarking methods for printed documents and digital images in two categories: those that embed visible patterns mimicking conventional paper watermarks and those that carry data. For each of these cases, we use visual demonstrations to highlight how an understanding of human perception and electronic imaging enables new applications.

Color Barcodes for Mobile and Other Applications

A framework is presented for extending monochrome barcodes popular for mobile applications to color. By advantageously exploiting the spectral diversity inherent in color printing/display and in the color capture by smartphone cameras, simple channel-by-channel color versions of common barcodes are obtained that offer three times the data rate while maintaining the robustness of monochrome barcodes.

High Capacity Data Hiding for Printed Images

A high capacity technique is presented for data-hiding in printed images and applied to the challenging technical problem of authenticating image content communicated over the analog printing channels commonly used for legal documents, The methodology allows localization of changes and fixes some fundamental limitations of prior robust hash based schemes.

Publication Etiquette and Ethics: Things You Should Know Before Submitting Your First Paper

Publishing the first research paper is usually an exciting experience for most researchers. In this excitement, it is important to not forget that the writing process for the first few manuscripts also often lays the ground for future habits. This presentation provides a guide to established etiquette and ethics in scholarly publishing for new and budding authors so they can learn the ropes without personally encountering common pitfalls and obstacles.

Initiating Research Effectively: A Guide and Personal Perspectives

Transitioning to research from course-work is frequently challenging for graduate students because research is less structured than most courses and involves significantly more uncertainty in the outcomes. In this presentation, we outline some promising strategies for graduate students.

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